Projection radiography accounts for over 60% of procedures in diagnostic radiology. As digital imaging becomes more important in daily radiology practice, the need for converting images from projection radiography to digital format becomes apparent. Currently four digital methods are being used: digital fluorography (DF), film digitization, and computed radiography, and direct digital radiography. Digital fluorography uses a vidicon camera to capture X-ray images and convert them to digital images through a frame grabber. One type of film digitizer uses a laser beam to convert the optical densities on film to a digital image. Computed radiography (CR) aims to replace screen/film analog radiographs with direct digital images. The imaging plate (IP) used in CR is based on the principle of laser-stimulable phosphor technology. Direct digital radiography is a recently developed direct digital capturing method which converts the attenuated x-rays directly from solid state detectors to digital signals. During the past ten years, CR has been gradually replacing the screen/film system.
Under normal operating conditions, images obtained by projection radiography contain unexposed areas due to X-ray collimation: for example, areas outside the circle of the imaging field in DF and areas outside the collimator of CR for skeletal and pediatric radiology. In digital images, unexposed areas appearing white on a display monitor will be called background in this context. FIG. 7 is a pediatric CR image with white background as seen on a monitor. Background removal in this context means that the brightness of the background is converted from white to black.
There are four major advantages gained by performing background removal in digital projection radiography. First, background removal immediately provides lossless data compression, an important cost-effective parameter in digital radiography when dealing with large-size images. Second, a background-removed image has better image visual quality for the following reason. Diagnosis from radiography is the result of information processing based on observation with the eye. Since the contrast sensitivity of the eye is proportional to the Weber ratio DB/B, where B is brightness of the background, and DB is brightness difference between the region of interest in the image and the background, removing or decreasing the unwanted background in projection radiography images makes these images more easily readable and greatly improves their diagnostic effects. Third, once the background in a CR image is removed, a more representative lookup table pertinent to only the range of gray scales in the image and not the background can be assigned to the image. Thus, it can improve the perception of the images. Fourth, background removal is a crucial pre-processing step in computer-aided-diagnosis (CAD). A background-removed image can improve the diagnostic accuracy of CAD algorithms, as the cost functions in the algorithms can be assigned to the image only rather than to the image and its background combined.
In the cases of DF and the film digitizer, the background removal procedure is straightforward. In the former, since the size of the image field is a predetermined parameter, the background can be removed by converting every pixel outside the diameter of the image field to black. In the latter, since the digital image is obtained in a two-step procedure (first a film is obtained and then the film is digitized), the boundaries between the background and the exposed area can be determined interactively by the user, and the corner points may be input during the digitizing step.
In the case of CR, background removal is a more complex procedure since it has to be done automatically during image acquisition or preprocessing time. Automatic removal of CR background is difficult, because the removal algorithm has to recognize different body part contours as well as various collimator sizes and shapes. Since the background distribution in CR images is complex and the removal is an irreversible procedure, it is difficult to achieve a high successful ratio of full background removal and yet ensure that no valid information in the image is removed. Full background removal in this context means that no more background is left in the processed image. Some methods developed to remove the background of CR images can only achieve 42% background removal.
Usually, the background in CR images is created due to the X-ray collimator. FIG. 14 shows the X-ray imaging procedure of a pediatric patient. Most collimators may be considered as attenuators of X-rays. Depending on the sensitivity of the imaging plate (IP) to x-rays and the thickness of the collimator used, the background may not be of uniform intensity due to various body parts covered by the collimator. First, let us ignore the anatomical information in the CR background and assume that the X-ray beam is a point source as shown in FIG. 15A. Then the intensity distribution, I, is spherical function and can be described by: EQU I=a cos.sup.2 .theta./r.sup.2 ( 1)
where "r" is distance between the source and IP center, ".theta." is the angle between the pixel under consideration and the center line in the plane defined by the pixel under consideration and the center line, and "a" is a constant, as shown in FIG. 15A. The intensity distribution of uniform latent image stored in IP is shown in FIG. 15B. After laser scanning the IP, the optical image generated from the latent image is converted to a digital image and the intensity distribution is shown in FIG. 15C.